The RAST Server: Rapid Annotations using Subsystems Technology

By Ramy Karam Aziz, D. Bartels, Aaron A. Best, M. DeJongh, T. Disz, Robert A. Edwards, Kevin Formsma, S. Gerdes, Elizabeth M. Glass, Michael Kubal and 16 more. BMC Genomics, 2008

11,377 citations recorded by the source corpus.

BackgroundThe number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them.DescriptionWe describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment.The service normally makes the annotated genome available within 12–24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service.ConclusionBy providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/535e3dd8ff4ae2ddcb7d1053913ffa09ee3f913c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Molecular Biology

Citations in the corpus

The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST) (2013, methodology): “RAST, Rapid Annotations using Subsystems Technology (8), is an automatic annotation server for microbial genomes, built upon the framework provided by the SEED system.”
Next generation sequencing and bioinformatic bottlenecks: the current state of metagenomic data analysis. (2012, methodology): “Online metagenome annotation services such as IMG-M [29] and MG-RAST [30], are also available.”
The Pangenome: Diversity, Dynamics and Evolution of Genomes (2020, background): “4 Frequency of reference to programs over the past 5 years in pangenome publications (referenced at least 4 times) The Bacterial Guide to Designing a Diversified Gene Portfolio 55 Prokka, PHAST, and Prodigal) (Aziz et al. 2008; Seemann 2014; Zhou et al. 2011; Hyatt et al. 2010), genome/gene alignmen”
Multi-Layer and Recursive Neural Networks for Metagenomic Classification (2015, methodology): “The microbiome data was obtained from the MG-RAST server [42], which hosts a large database of metagenomes and tools for analyzing and comparing them.”
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions (2010, background): “Because of the great effort involved, there have been attempts to partially automate the process [25-31] and split work through collaboration [32].”
Prokka: rapid prokaryotic genome annotation (2014, positive): “RAST is a web server for annotating bacterial and archaeal genomes that provides annotation results in under a day (Aziz et al. , 2008), and xBASE2 does similar in a few hours (Chaudhuri et al. , 2008).”
Taxonomical and functional microbial community selection in soybean rhizosphere (2014, methodology): “Taxonomic and functional profiles were generated using the normalized abundance of sequence matches to the SEED database (Aziz et al., 2008).”
ARG-ANNOT, a New Bioinformatic Tool To Discover Antibiotic Resistance Genes in Bacterial Genomes (2013, methodology): “Rapid Annotation using Subsystem Technology (RAST) is one of the most widely used servers for bacterial genome annotation (2).”
The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities (2019, methodology): “This distribution is available for Mac, Windows and Linux operating systems, including Ubuntu and Cen-tOS 6 and 7, and Fedora 28 and 29 (https://github.com/ PATRIC3/PATRIC-distribution/releases).”
BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences. (2016, methodology): “Brief comparisons are made to other servers including KAAS [4], RAST [5] and MG-RAST [6].”